# move known formation energies to the other side known_columns = [] dG0_f = zeros((len(all_cids), 1)) for c in xrange(len(all_cids)): if (all_cids[c] in [101, 2051]): # define as 0 (THF and LP) known_columns.append(c) dG0_f[c, 0] = 0 elif (all_cids[c] in [ 440, 234, 143, 445, 2972, 1242, 6020, 6021 ]): # although GC can calculate it, I'd rather not use that value continue else: try: temp = G.estimate_dG0_keggcid(all_cids[c], pH=7.0, I=0.25, T=298.15) #temp = G.estimate_dG0_keggcid(all_cids[c], pH=7.0, I=0.0, T=311) known_columns.append(c) dG0_f[c, 0] = temp except Exception: continue unknown_columns = sorted( list(set(range(len(all_cids))).difference(known_columns)) ) # find all the indices of columns not in known_columns unknown_rows = find(isnan(dG0_r)) known_rows = sorted(list(set(range(len(reactions))).difference( unknown_rows))) # find all the indices of rows with measured dG0_r S_measured = S[known_rows, :]
c = all_cids.index(cid) S[r, c] = coeff dG0_r[r, 0] = reactions[r][3] # move known formation energies to the other side known_columns = [] dG0_f = zeros((len(all_cids), 1)) for c in xrange(len(all_cids)): if (all_cids[c] in [101, 2051]): # define as 0 (THF and LP) known_columns.append(c) dG0_f[c, 0] = 0 elif (all_cids[c] in [440, 234, 143, 445, 2972, 1242, 6020, 6021]): # although GC can calculate it, I'd rather not use that value continue else: try: temp = G.estimate_dG0_keggcid(all_cids[c], pH=7.0, I=0.25, T=298.15) #temp = G.estimate_dG0_keggcid(all_cids[c], pH=7.0, I=0.0, T=311) known_columns.append(c) dG0_f[c, 0] = temp except Exception: continue unknown_columns = sorted(list(set(range(len(all_cids))).difference(known_columns))) # find all the indices of columns not in known_columns unknown_rows = find(isnan(dG0_r)) known_rows = sorted(list(set(range(len(reactions))).difference(unknown_rows))) # find all the indices of rows with measured dG0_r S_measured = S[known_rows, :] b = dG0_r[known_rows] - dot(S_measured[:, known_columns], dG0_f[known_columns]) S_red = S_measured[:, unknown_columns] print "Formation energies from from GC and from linear regression: "